Physical adversarial attacks in object detection have attracted increasing
attention. However, most previous works focus on hiding the objects from the
detector by generating an individual adversarial patch, which only covers the
planar part of the vehicle's surface and fails to attack the detector in
physical scenarios for multi-view, long-distance and partially occluded
objects. To bridge the gap between digital attacks and physical attacks, we
exploit the full 3D vehicle surface to propose a robust Full-coverage
Camouflage Attack (FCA) to fool detectors. Specifically, we first try rendering
the nonplanar camouflage texture over the full vehicle surface. To mimic the
real-world environment conditions, we then introduce a transformation function
to transfer the rendered camouflaged vehicle into a photo realistic scenario.
Finally, we design an efficient loss function to optimize the camouflage
texture. Experiments show that the full-coverage camouflage attack can not only
outperform state-of-the-art methods under various test cases but also
generalize to different environments, vehicles, and object detectors. The code
of FCA will be available at:
this https URL

为了攻击更多的实际场景中的目标检测器，本文利用全覆盖的伪装攻击（FCA）在全车 3D 曲面内渲染非平面伪装纹理，然后将其转换为真实场景。实验表明，这种攻击不仅在不同的测试环境、不同的车辆和目标检测器中都比现有方法更优秀，而且具有一般性。